Overview

Dataset statistics

Number of variables2
Number of observations22
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory506.0 B
Average record size in memory23.0 B

Variable types

Numeric1
Text1

Dataset

Description전라남도 순천시 지방세 ARS 수납시스템 은행코드 데이터로, 22개의 은행에 대한 은행코드와 은행명 항목을 제공합니다.
Author전라남도 순천시
URLhttps://www.data.go.kr/data/15063592/fileData.do

Alerts

은행코드 has unique valuesUnique
은행명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 17:03:30.733858
Analysis finished2023-12-12 17:03:31.112058
Duration0.38 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

은행코드
Real number (ℝ)

UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean32.045455
Minimum2
Maximum88
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2023-12-13T02:03:31.197637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile3.05
Q111.25
median31.5
Q343.5
95-th percentile80.5
Maximum88
Range86
Interquartile range (IQR)32.25

Descriptive statistics

Standard deviation24.751099
Coefficient of variation (CV)0.77237471
Kurtosis0.15237176
Mean32.045455
Median Absolute Deviation (MAD)17.5
Skewness0.81169439
Sum705
Variance612.61688
MonotonicityStrictly increasing
2023-12-13T02:03:31.755991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
2 1
 
4.5%
34 1
 
4.5%
88 1
 
4.5%
81 1
 
4.5%
71 1
 
4.5%
50 1
 
4.5%
48 1
 
4.5%
45 1
 
4.5%
39 1
 
4.5%
37 1
 
4.5%
Other values (12) 12
54.5%
ValueCountFrequency (%)
2 1
4.5%
3 1
4.5%
4 1
4.5%
5 1
4.5%
7 1
4.5%
11 1
4.5%
12 1
4.5%
20 1
4.5%
23 1
4.5%
27 1
4.5%
ValueCountFrequency (%)
88 1
4.5%
81 1
4.5%
71 1
4.5%
50 1
4.5%
48 1
4.5%
45 1
4.5%
39 1
4.5%
37 1
4.5%
35 1
4.5%
34 1
4.5%

은행명
Text

UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size308.0 B
2023-12-13T02:03:31.993889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length4
Mean length4.3181818
Min length2

Characters and Unicode

Total characters95
Distinct characters50
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)100.0%

Sample

1st row산업은행
2nd row기업은행
3rd row국민은행
4th row외환은행
5th row수협
ValueCountFrequency (%)
산업은행 1
 
4.5%
기업은행 1
 
4.5%
하나(서울)은행 1
 
4.5%
우체국 1
 
4.5%
상호저축은행 1
 
4.5%
신협 1
 
4.5%
새마을금고 1
 
4.5%
경남은행 1
 
4.5%
전북은행 1
 
4.5%
제주은행 1
 
4.5%
Other values (12) 12
54.5%
2023-12-13T02:03:32.357517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
은 16
 
16.8%
행 16
 
16.8%
협 4
 
4.2%
산 2
 
2.1%
회 2
 
2.1%
신 2
 
2.1%
주 2
 
2.1%
업 2
 
2.1%
한 2
 
2.1%
( 2
 
2.1%
Other values (40) 45
47.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 91
95.8%
Open Punctuation 2
 
2.1%
Close Punctuation 2
 
2.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
은 16
 
17.6%
행 16
 
17.6%
협 4
 
4.4%
산 2
 
2.2%
회 2
 
2.2%
신 2
 
2.2%
주 2
 
2.2%
업 2
 
2.2%
한 2
 
2.2%
제 2
 
2.2%
Other values (38) 41
45.1%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 91
95.8%
Common 4
 
4.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
은 16
 
17.6%
행 16
 
17.6%
협 4
 
4.4%
산 2
 
2.2%
회 2
 
2.2%
신 2
 
2.2%
주 2
 
2.2%
업 2
 
2.2%
한 2
 
2.2%
제 2
 
2.2%
Other values (38) 41
45.1%
Common
ValueCountFrequency (%)
( 2
50.0%
) 2
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 91
95.8%
ASCII 4
 
4.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
은 16
 
17.6%
행 16
 
17.6%
협 4
 
4.4%
산 2
 
2.2%
회 2
 
2.2%
신 2
 
2.2%
주 2
 
2.2%
업 2
 
2.2%
한 2
 
2.2%
제 2
 
2.2%
Other values (38) 41
45.1%
ASCII
ValueCountFrequency (%)
( 2
50.0%
) 2
50.0%

Interactions

2023-12-13T02:03:30.830832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T02:03:32.458106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
은행코드은행명
은행코드1.0001.000
은행명1.0001.000

Missing values

2023-12-13T02:03:30.978877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T02:03:31.072980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

은행코드은행명
02산업은행
13기업은행
24국민은행
35외환은행
47수협
511농협중앙회
612회원농협
720우리은행
823제일은행
927씨티(한미)은행
은행코드은행명
1234광주은행
1335제주은행
1437전북은행
1539경남은행
1645새마을금고
1748신협
1850상호저축은행
1971우체국
2081하나(서울)은행
2188신한은행